Kybernetik og systemteori

Discover a powerful new lens for viewing the world with fascinating implications for our companies, economies, societies, and planet as a whole.What causes one system to break down and another to rebound? Are we merely subject to the whim of forces beyond our control? Or, in the face of constant disruption, can we build better shock absorbers—for ourselves, our communities, our economies, and for the planet as a whole? Reporting firsthand from the coral reefs of Palau to the back streets of Palestine, Andrew Zolli and Ann Marie Healy relate breakthrough scientific discoveries, pioneering social and ecological innovations, and important new approaches to constructing a more resilient world. Zolli and Healy show how this new concept of resilience is a powerful lens through which we can assess major issues afresh: from business planning to social develop­ment, from urban planning to national energy security—circumstances that affect us all. Provocative, optimistic, and eye-opening, Resilience sheds light on why some systems, people, and communities fall apart in the face of disruption and, ultimately, how they can learn to bounce back.

Wie kann man Ressourcen optimal nutzen? Wie finde ich die richtige Losung fur ein kompliziertes Problem? Wie erreiche ich mit geringstem Aufwand mein Ziel?Ohne mathematische Formeln zu bemuhen, geht der Autor diesen und anderen Fragen der Optimierung komplexer Systeme auf den Grund. Die betrachteten Anwendungsfalle reichen von Ablaufplanungen uber den Aufbau eines Energienetzes und anderer technischer Strukturen bis hin zu Fragen des taglichen Lebens - wie dem leidigen Kofferpacken oder frustrierten Beziehungen.Leicht verstandlich und gut illustriert werden effiziente Herangehensweisen an die verschiedensten Optimierungsprobleme beschrieben und zahlreiche Algorithmen zu ihrer Losung vorgestellt. Auf fast spielerische Weise betrachtet der Autor von einem einheitlichen Standpunkt aus kombinatorische wie kontinuierliche Optimierungsfragen und schlagt zum Schluss einen Bogen zur philosophischen Betrachtung uber die Schonheit unserer Welt.

You may know that the Quantum Theory revolutionized our perception of matter on the atomic scale, but did you know that its founder, Max Planck, himself didn't believe it?This short read is Planck's address to the Royal Swedish Academy of Sciences after winning the Nobel prize. He displays how his Quantum Theory came into existence. It was not the result of a single lab experiment and a conclusion, but an inspection of overwhelming evidence from various works of immortal names like Bohr, Hertz, Ostwald, Einstein, and others.Planck unveils secrets in the scientific community, explains why his own theory was inconceivable to the classical physicist, and first mentions the famous dispute between Quantum Theory and Relativity in this eye-opening book."After some weeks of the most intense work of my life, clearness began to dawn upon me, and an unexpected view revealed itself in the distance.""The quantum would have to play a fundamental role in physics, heralding the advent of a new state of things, destined to transform completely our physical concepts." ~Max Planck

This book describes recent findings in the domain of Boolean logic and Boolean algebra, covering application domains in circuit and system design, but also basic research in mathematics and theoretical computer science. Content includes invited chapters and a selection of the best papers presented at the 14th annual International Workshop on Boolean Problems.

This book applies artificial intelligence to lean production and shows how to practically combine the advantages of these two disciplines. Lean manufacturing originated in Japan and is a well-known tool for improving manufacturers' competitiveness. Prevalent tools for lean manufacturing include Kanban, Pacemaker, Value Stream Map, 5s, Just-in-Time and Pull Manufacturing. Lean Manufacturing and  the Toyota Manufacturing System has been successfully applied to various factories and supply chains around the world. A lean manufacturing system can not only reduce wastes and inventory, but also respond to customer needs more immediately. Artificial intelligence is a subject that has attracted much attention recently. Many researchers and practical developers are working hard to apply artificial intelligence to our daily lives, including in factories. For example, fuzzy rules have been established to optimize machine settings. Bionic algorithms have been proposed to solve production sequencing and scheduling problems. Machine learning technologies are applied to detect possible product quality problems and diagnose the health of a machine. This book will be of interest to production engineers, managers, as well as students and researchers in manufacturing engineering.

This book highlights the prevention of possible accidents and crashes of aircrafts by analyzing the many factors that affect such events. It includes the theoretical study of known ideas and concepts, as well as a set of new methods and mathematical models. It contains factual information to investigate famous disasters and aviation accidents with aircrafts. The book proposes methods and models that can be the basis in developing guidance material for decision-making by the flight crew and experts in air traffic control. Some of the contents presented in this book are also useful in the design and operation of data transmission systems of aircraft. The book is intended for engineering and technical specialists engaged in the development, manufacturing and operations of onboard radio electronic systems of aircraft and ground-based radio engineering support for flights, as well as graduate students and senior students of radio engineering specialties. It is useful to researchers and managers whose activities are related to air traffic control.

This book explores recent advances in the Internet of things (IoT) via advanced technologies and provides an overview of most aspects which are relevant for advance secure, distributed, decentralized blockchain technology in the Internet of things, their applications, and industry IoT. The book provides an in-depth analysis of the step-by-step evolution of IoT to create a change by enhancing the productivity of industries. It introduces how connected things, data, and their communication (data sharing) environment build a transparent, reliable, secure environment for people, processes, systems, and services with the help of blockchain technology.

With the goal of establishing a version for partial differential equations (PDEs) of the Aubry-Mather theory of monotone twist maps, Moser and then Bangert studied solutions of their model equations that possessed certain minimality and monotonicity properties. This monograph presents extensions of the Moser-Bangert approach that include solutions of a family of nonlinear elliptic PDEs on Rn and an Allen-Cahn PDE model of phase transitions. After recalling the relevant Moser-Bangert results, Extensions of Moser-Bangert Theory pursues the rich structure of the set of solutions of a simpler model case, expanding upon the studies of Moser and Bangert to include solutions that merely have local minimality properties. Subsequent chapters build upon the introductory results, making the monograph self contained.Part I introduces a variational approach involving a renormalized functional to characterize the basic heteroclinic solutions obtained by Bangert. Following that, Parts II and III employ these basic solutions together with constrained minimization methods to construct multitransition heteroclinic and homoclinic solutions on R×Tn-1 and R2×Tn-2, respectively, as local minima of the renormalized functional. The work is intended for mathematicians who specialize in partial differential equations and may also be used as a text for a graduate topics course in PDEs.

Fracture, Fatigue, Failure and Damage Evolution, Volume 3 of the Proceedings of the 2020 SEM Annual Conference & Exposition on Experimental and Applied Mechanics, the third volume of seven from the Conference, brings together contributions to this important area of research and engineering. The collection presents early findings and case studies on a wide range of areas, including:Novel Experimental MethodsExtreme EnvironmentsInterfacial FractureIntegration of Models & ExperimentsMechanics of Energy & Energetic MaterialsIntegration of Models & ExperimentsIn Situ Techniques for Fatigue & FractureMicroscale & Microstructural Effects on Mechanical Behavior

Fachbuch aus dem Jahr 2017 im Fachbereich Philosophie - Theoretische (Erkenntnis, Wissenschaft, Logik, Sprache), Note: 1,7, AKAD University, ehem. AKAD Fachhochschule Stuttgart, Veranstaltung: Systematisches Denken und Handeln, Sprache: Deutsch, Abstract: System Dynamics (SD) ist eine von dem US-amerikanischen Elektroingenieur Jay W. FORRESTER (1918¿2016) entwickelte kybernetische Simulationsmethode zur ganzheitlichen Analyse komplexer, nicht linearer kontinuierlicher Systeme. In der deutschsprachigen Fachliteratur wird System Dynamics mit Systemdynamik übersetzt. In der Wirtschaftswissenschaft haben sich jedoch auch die Synonyme Business Dynamics oder Strategy Dynamics etabliert. FORRESTER schloss sich 1956 der Sloan Management School am Massachusetts Institute of Technology (MIT) an. Hier sah er die einmalige Chance, Ingenieurs- mit Wirtschaftswissenschaften in Forschung und Lehre zu kombinieren. Ausschlaggebend für seine weiterführende Tätigkeit am MIT war die Zusammenarbeit mit dem Management von General Electric. Hier stellte er fest, dass bei der Suche nach Gründen für die Auslastungsschwierigkeiten eines Werkes ¿ also einem betriebswirtschaftlichen Problem ¿ sein Wissen aus dem Ingenieurswesen half die Problemstellung zu lösen. Die Situation wurde in einem formalen Modell abgebildet und ihre zeitliche Entwicklung mit Hilfe eines Computers simuliert. FORRESTER bemerkte dabei, dass viele Probleme eine generische Systemstruktur aufwiesen und veröffentlichte daraufhin sein Werk Industrial Dynamics. Dieses gilt auch heute noch als Standardwerk, an dem sich Forschung und Lehre orientieren können. Obwohl SD ursprünglich für die Lösung ingenieurwissenschaftlicher Problemstellungen gedacht war, findet sie mittlerweile auch Anwendung in vielen anderen Fachdisziplinen, wie Unternehmensentwicklung, Medizin, Fischerei, Psychiatrie, Energieversorgung und -preisgestaltung, Volkswirtschaften, städtischem Wachstum, Umweltverschmutzung, Bevölkerungswachstum, Managementtraining sowie Pädagogik. Diese Ausarbeitung hat zum Ziel, einen Einblick in die von FORRESTER entwickelte Methode System Dynamics zu gewähren. Dazu befassen wir uns im zweiten Kapitel zunächst mit der Definition der Begriffe Modell, System, Kybernetik und Simulation. Im dritten Kapitel gehen wir detailliert auf FORRESTERS System Dynamics Methodik ein. Hier erläutern wir zunächst die Grundlagen, gehen dann auf die qualitative und quantitative Modellierung ein und präsentieren eine praktische Einsatzmöglichkeit zu der Methode. Abschließend wird im letzten Kapitel ein Fazit gezogen und eine kritische Würdigung vorgenommen.

Optimal Control brings together many of the important advances in 'nonsmooth' optimal control over the last several decades concerning necessary conditions, minimizer regularity, and global optimality conditions associated with the Hamilton–Jacobi equation. The book is largely self-contained and incorporates numerous simplifications and unifying features for the subject’s key concepts and foundations.Features and Topics:* a comprehensive overview is provided for specialists and nonspecialists* authoritative, coherent, and accessible coverage of the role of nonsmooth analysis in investigating minimizing curves for optimal control* chapter coverage of dynamic programming and the regularity of minimizers* explains the necessary conditions for nonconvex problemsThis book is an excellent presentation of the foundations and applications of nonsmooth optimal control for postgraduates, researchers, and professionals in systems, control, optimization, and applied mathematics.-----Each chapter contains a well-written introduction and notes. They include the author's deep insights on the subject matter and provide historical comments and guidance to related literature. This book may well become an important milestone in the literature of optimal control.—Mathematical ReviewsThis remarkable book presents Optimal Control seen as a natural development of Calculus of Variations so as to deal with the control of engineering devices. ... Thanks to a great effort to be self-contained, it renders accessibly the subject to a wide audience. Therefore, it is recommended to all researchers and professionals interested in Optimal Control and its engineering and economic applications. It can serve as an excellent textbook for graduate courses in Optimal Control (with special emphasis on Nonsmooth Analysis). —AutomaticaThe book may be an essential resource for potential readers, experts in control and optimization, as well as postgraduates and applied mathematicians, and it will be valued for its accessibility and clear exposition.—Applications of Mathematics

For over 300 years, differential equations have served as an essential tool for describing and analyzing problems in many scientific disciplines. This carefully-written textbook provides an introduction to many of the important topics associated with ordinary differential equations. Unlike most textbooks on the subject, this text includes nonstandard topics such as a chapter on perturbation methods and a section in Chapter 3 that shows how to solve differential equations using Mathematica codes. In addition to the nonstandard topics, this text also contains contemporary material in the area as well as its classical topics.This second edition is updated to be compatible with Mathematica, version 7.0, and all Mathematica codes are in the book itself. This new edition also provides 81 additional exercises, a new section in Chapter 1 on the generalized logistic equation, an additional theorem in Chapter 2 concerning fundamental matrices, and many further enhancements to the first edition.This book can be used either for a second course in ordinary differential equations or as an introductory course for well-prepared students. The prerequisites for this book are three semesters of calculus and a course in linear algebra, although the needed concepts from linear algebra are introduced along with examples in the book. An undergraduate course in analysis is needed for the more theoretical subjects covered in the final two chapters.

This volume includes papers presented at the Third Annual Computation and Neural Systems meeting (CNS*94) held in Monterey California, July 21 - July 26, 1994. This collection includes 71 of the more than 100 papers presented at this year's meeting. Acceptance for meeting presentation was based on the peer review of preliminary papers by at least two referees. The papers in this volume were submitted in final form after the meeting. As represented by this volume, CNS meetings continue to expand in quality, size and breadth of focus as increasing numbers of neuroscientists are taking a computational approach to understanding nervous system function. The CNS meetings are intended to showcase the best of current research in computational neuroscience. As such the meeting is fundamentally focused on understanding the relationship between the structure of neIVOUS systems and their function. What is clear from the continued expansion of the CNS meetings is that computational approaches are increasingly being applied at all levels of neurobiological analysis. in an ever growing number of experimental preparations. and neural subsystems. Thus. experimental subjects range from crickets to primates; sensory systems range from vision to electroreception; experimental approaches range from realistic models of ion channels to the analysis of the information content of spike trains. For this reason, the eNS meetings represent an opportunity for computational neurobiologists to consider their research results in a much broader context than is usually possible.

The problem of controlling or stabilizing a system of differential equa­ tions in the presence of random disturbances is intuitively appealing and has been a motivating force behind a wide variety of results grouped loosely together under the heading of "Stochastic Control." This book is concerned with a special instance of this general problem, the "Adaptive LQ Regulator," which is a stochastic control problem of partially observed type that can, in certain cases, be solved explicitly. We first describe this problem, as it is the focal point for the entire book, and then describe the contents of the book. The problem revolves around an uncertain linear system x(O) = x~ in R", where 0 E {1, ... , N} is a random variable representing this uncertainty and (Ai' B , C) and xJ are the coefficient matrices and initial state, respectively, of j j a linear control system, for eachj = 1, ... , N. A common assumption is that the mechanism causing this uncertainty is additive noise, and that conse­ quently the "controller" has access only to the observation process y( . ) where y = Cex +~.

Topological bifurcation theory is one of the most essential topics in mathematics. This book contains original bifurcation results for the existence of oscillations and chaotic behaviour of differential equations and discrete dynamical systems under variation of involved parameters. Using topological degree theory and a perturbation approach in dynamical systems, a broad variety of nonlinear problems are studied, including: non-smooth mechanical systems with dry frictions; weakly coupled oscillators; systems with relay hysteresis; differential equations on infinite lattices of Frenkel-Kontorova and discretized Klein-Gordon types; blue sky catastrophes for reversible dynamical systems; buckling of beams; and discontinuous wave equations. Precise and complete proofs, together with concrete applications with many stimulating and illustrating examples, make this book valuable to both the applied sciences and mathematical fields, ensuring the book should not only be of interest to mathematicians but to physicists and theoretically inclined engineers interested in bifurcation theory and its applications to dynamical systems and nonlinear analysis.

The million-copy bestseller by National Book Award nominee and Pulitzer Prize finalist James Gleick-the author of Time Travel: A History-that reveals the science behind chaos theoryA work of popular science in the tradition of Stephen Hawking and Carl Sagan, this 20th-anniversary edition of James Gleick's groundbreaking bestseller Chaos introduces a whole new readership to chaos theory, one of the most significant waves of scientific knowledge in our time. From Edward Lorenz's discovery of the Butterfly Effect, to Mitchell Feigenbaum's calculation of a universal constant, to Benoit Mandelbrot's concept of fractals, which created a new geometry of nature, Gleick's engaging narrative focuses on the key figures whose genius converged to chart an innovative direction for science. In Chaos, Gleick makes the story of chaos theory not only fascinating but also accessible to beginners, and opens our eyes to a surprising new view of the universe.

Physicists, when modelling physical systems with a large number of degrees of freedom, and statisticians, when performing data analysis, have developed their own concepts and methods for making the `best' inference. But are these methods equivalent, or not? What is the state of the art in making inferences? The physicists want answers. More: neural computation demands a clearer understanding of how neural systems make inferences; the theory of chaotic nonlinear systems as applied to time series analysis could profit from the experience already booked by the statisticians; and finally, there is a long-standing conjecture that some of the puzzles of quantum mechanics are due to our incomplete understanding of how we make inferences. Matter enough to stimulate the writing of such a book as the present one. But other considerations also arise, such as the maximum entropy method and Bayesian inference, information theory and the minimum description length. Finally, it is pointed out that an understanding of human inference may require input from psychologists. This lively debate, which is of acute current interest, is well summarized in the present work.

This is the ?rst in a series of three volumes dedicated to the lecture notes of the Summer School "e;Open Quantum Systems"e; which took place at the Institut Fourier in Grenoble from June 16th to July 4th 2003. The contributions presented in these volumes are revised and expanded versions of the notes provided to the students during the School. Closed vs. Open Systems By de?nition, the time evolution of a closed physical systemS is deterministic. It is usually described by a differential equation x ? = X(x ) on the manifold M of t t possible con?gurations of the system. If the initial con?guration x ? M is known 0 then the solution of the corresponding initial value problem yields the con?guration x at any future time t. This applies to classical as well as to quantum systems. In the t classical case M is the phase space of the system and x describes the positions and t velocities of the various components (or degrees of freedom) ofS at time t. Inthe quantum case, according to the orthodox interpretation of quantum mechanics, M is a Hilbert space and x a unit vector - the wave function - describing the quantum t state of the system at time t. In both cases the knowledge of the state x allows t to predict the result of any measurement made onS at time t.

This volume presents revised and extended versions of selected papers presented at the Joint Workshop on Multi-Agent and Multi-Agent-Based Simulation, a workshop federated with the 3rd International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2004), which was held in New York City, USA, July 19-23, 2004. The workshop was in part a continuation of the International Workshop on Multi-Agent-Based Simulation (MABS) series. - vised versions of papers presented at the four previous MABS workshops have been published as volumes 1534, 1979, 2581, and 2927 in the Lecture Notes in Arti?cial Intelligence series. The aim of the workshop was to provide a forum for work in both appli- tions of multi-agent-based simulation and the technical challenges of simulating large multi-agent systems (MAS). There has been considerable recent progress in modelling and analyzing multi-agent systems, and in techniques that apply MAS models to complex real-world systems such as social systems and organi- tions. Simulation is an increasingly important strand that weaves together this work. In high-risk, high-cost situations, simulations provide critical cost/bene?t leverage, and make possible explorations that cannot be carried out in situ: - Multi-agentapproachestosimulatingcomplexsystemsarekeytoolsinint- disciplinary studies of social systems. Agent-based social simulation (ABSS) researchsimulatesandsynthesizessocialbehaviorinordertounderstandreal social systems with properties of self-organization, scalability, robustness, and openness. - IntheMAScommunity,simulationhasbeenappliedtoawiderangeofMAS research and design problems, from models of complex individual agents - ploying sophisticated internal mechanisms to models of large-scale societies of relatively simple agents which focus more on the interactions between agents.

The problem of deriving irreversible thermodynamics from the re­ versible microscopic dynamics has been on the agenda of theoreti­ cal physics for a century and has produced more papers than can be digested by any single scientist. Why add to this too long list with yet another work? The goal is definitely not to give a gen­ eral review of previous work in this field. My ambition is rather to present an approach differing in some key aspects from the stan­ dard treatments, and to develop it as far as possible using rather simple mathematical tools (mainly inequalities of various kinds). However, in the course of this work I have used a large number of results and ideas from the existing literature, and the reference list contains contributions from many different lines of research. As a consequence the reader may find the arguments a bit difficult to follow without some previous exposure to this set of problems.

In this monograph, nonequilibrium statistical mechanics is developed by means of ensemble methods on the basis of the Boltzmann equation, the generic Boltzmann equations for classical and quantum dilute gases, and a generalised Boltzmann equation for dense simple fluids. The theories are developed in forms parallel with the equilibrium Gibbs ensemble theory in a way fully consistent with the laws of thermodynamics. The generalised hydrodynamics equations are the integral part of the theory and describe the evolution of macroscopic processes in accordance with the laws of thermodynamics of systems far removed from equilibrium. Audience: This book will be of interest to researchers in the fields of statistical mechanics, condensed matter physics, gas dynamics, fluid dynamics, rheology, irreversible thermodynamics and nonequilibrium phenomena.